[future][discussion] how to incorporate external modules ?

Description of feature

Allow for data processing to be done by modules external from the stimulus-py package and not necessarily in python

Example :

Splitting a sequence dataset could be done using pairwise similarity + kmeans
There are many tools doing pairwise similarity, some even gpu accelerated, and some nf-core modules could do this

Current way to do this would be to wrap the method in python and bumb the pip package but it isn't the nf-core way, it would be much better if instead, we could re-use modules with some minor overhead for format/data processing.

This should be done while considering :

1. whether the tool should be ran or not depends on the experiment config
2. code should be kept clean (there are many tools that could interface with data processing - and the number will keep growing ), chaining IF/ELSE is not an option
3. good error handling (i.e. blast can't run on images for instance)

No files, tests, or entry points are named. Start by locating the experiment configuration and the current data-processing flow in stimulus-py, then determine how external modules would be selected, chained, and validated. Done should include a decided integration design covering conditional execution, clean extensibility, and errors such as BLAST receiving images.